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Build and maintain the AI platform infrastructure, including Kubernetes, vector databases, and real-time monitoring, using Java, Azure, and AI tools like GitHub Copilot.
Builds low-level system software to optimize distributed AI training and inference across thousands of GPUs using C++, Python, and CUDA.
Build and deploy AI/ML models, focusing on language technologies like NLP and dialogue systems using Python, PyTorch, and Hugging Face frameworks.
Build and own the AI inference pipeline that connects Life360’s deterministic backend with LLMs, designing model selection, serving infrastructure, and evaluation loops to power an intelligent family operating system.
Principal engineer leading backend and ML infrastructure at a Series C conversational AI company, designing real-time data pipelines, scaling GPU fleets, and optimizing inference costs for enterprise speech/NLP systems.
Разработчик поддерживает и развивает высоконагруженную LLM-платформу на .NET, Python и React, оптимизируя инференс, PostgreSQL и GPU-инфраструктуру для обработки текста, изображений и аудио.
Build and maintain automated testing and CI/CD infrastructure for a complex AI/ML software stack, ensuring reliability and performance across simulators, emulators, and hardware.
Lead a team to design, build, and deploy ML/AI systems for ecommerce search, recommendations, and personalization, shipping models that directly move business metrics.
Optimize inference for local LLMs and internal models using vLLM/Triton, manage GPU resources, and monitor high-load AI infrastructure for a logistics-focused AI company.
Build and deploy agentic AI workflows for legal SaaS, using FastAPI backends and LLM tooling to automate contract review and legal research.
ML engineer builds and runs online reinforcement-learning pipelines to improve GigaChat’s post-training, designing experiments, reward signals, and distributed training workflows.
Build AI agents and MCP servers that let LLMs autonomously use internal financial data; optimize GPU/CPU and storage for high-performance AI workloads; and implement end-to-end MLOps pipelines with RAG over knowledge graphs.
Designs and maintains cloud infrastructure using AWS/Azure/GCP, IaC (Terraform), Docker, and CI/CD pipelines to support scalable, secure, and cost-efficient solutions for development teams.
Разрабатывает пайплайны для сбора и обработки неструктурированных данных, настраивает LLM-агентов и ML/NLP модели для обогащения данных о российских компаниях.
Builds and maintains the core backend infrastructure for AI-powered hospital automation, including EMR/OCS integrations, API servers, and model-serving pipelines in a secure on-premise environment.
Design and deploy scalable, real-time AI systems including LLM inference pipelines, RAG, and vector databases using Python, TensorFlow/PyTorch, and Kubernetes.
Senior DevOps/SRE engineer building and scaling AWS-based IaC (Terraform, ECS/EKS) and CI/CD pipelines in Azure DevOps, while ensuring observability, security, and cost-efficiency for AI model deployments and data workloads.
About * Who we are Video is 90% of the world's data. Most of it is invisible to machines. TwelveLabs builds the intelligence layer to change that. Our multimodal AI models understand video the way humans do —…
Build and optimize the production serving stack for Jockey Core, TwelveLabs’ reasoning LLM that powers agentic video understanding across millions of hours of content.
Senior Full Stack developer and system architect building sovereign, eco-efficient AI infrastructure in Python/FastAPI and React/Next.js, integrating self-hosted LLMs and ensuring high availability and data sovereignty.
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